In recent years, the online advertising market has grown substantially to become one of the largest advertising markets in the world. As the value of online advertising increases, so does the importance of ensuring that appropriate advertisements are delivered to users in order to maximize success of advertisement campaigns. Under the increasingly common cost-per-click (CPC) model of payment, the number of times an advertisement was clicked determines the compensation provided to the website hosting the advertisement.
Due to the direct monetary value of high click rates, ensuring success of online advertisements has become essential to the online advertising market. A prevalent measure of advertisement campaign success is the click-through-rate (CTR). The CTR of an advertisement is equal to the ratio between the number of times an advertisement was clicked and the number of times the advertisement was presented to users. CTRs are typically used in conjunction with web banners (also referred to as online banner advertisements), in which such banners are embedded into webpages as static images. Such web banners are intended to attract traffic to advertisers' websites.
Online ad-serving relates to the placement of advertisements on webpages and/or within multimedia content. In addition to placing advertisements, advertisement serving systems also select which advertisements should be served to websites based on advertising campaign preferences, count impressions, click counts on advertisements, and monitored progress of different advertising campaigns. An advertisement serving system is typically realized as a server backed by a database server that stores advertisements.
In some existing solutions, the selection of which advertisements to serve on which webpages may be determined through an auction process. In such a process, advertisers bid for allocation and serving of their online advertisements in connection with serving opportunities. In online advertising, an auction process is typically realized by means of a real-time bidding (RTB) system. In some configurations, the advertisements may be served based on ad-exchange networks' predefined settings, and so on.
Existing solutions for predicting online advertising campaign success typically focus on keywords associated with advertisements to determine whether users of a particular website are likely to be interested in the advertisements. However, such solutions lack the ability to identify characteristics in advertisements that are not represented by keywords. Additionally, such solutions do not provide information on how to improve proposed advertisements before delivery.
Other solutions for predicting online advertising campaign success are based on demographics of a target audience. However, the creative aspects (i.e., the design) of the advertisements are usually not considered when determining potential success based on demographics.
As a result, a designer of an advertisement cannot design the creative aspects of the advertisement in such a way that would maximize advertisement campaign success. Specifically, this is the case for web banners and other image-based advertisements. For example, a designer cannot make an educated decision regarding whether to use a blue background or a red background so as to increase the reach and the success of the advertisement.
It would therefore be advantageous to provide a solution that would overcome the deficiencies of the prior art by predicting advertisement campaign success of at least image-based advertisements.